Evidence map›Paper›PMID 38087989›Full record

ReviewHuman vaccines & immunotherapeutics2023

CEA vaccines.

Anchit Bhagat, Herbert K Lyerly, Michael A Morse, Zachary C Hartman

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Human vaccines & immunotherapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.6field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Anchit BhagatDepartment of Surgery, Division of Surgical Sciences, Duke University, Durham, NC, USA.
Herbert K LyerlyDepartment of Surgery, Division of Surgical Sciences, Duke University, Durham, NC, USA.
Michael A MorseDepartment of Surgery, Division of Surgical Sciences, Duke University, Durham, NC, USA.
Zachary C HartmanDepartment of Surgery, Division of Surgical Sciences, Duke University, Durham, NC, USA.ORCID 0000-0001-6549-8207
Duke University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carcinoembryonic antigen (CEA) is a glycosylated cell surface oncofetal protein involved in adhesion, proliferation, and migration that is highly upregulated in multiple carcinomas and has long been a promising target for cancer vaccination. This review summarizes the progress to date in the development of CEA vaccines, examining both pre-clinical and clinical studies across a variety of vaccine platforms that in aggregate, begin to reveal some critical insights. These studies demonstrate the ability of CEA vaccines to break immunologic tolerance and elicit CEA-specific immunity, which associates with improved clinical outcomes in select individuals. Approaches that have combined replicating viral vectors, with heterologous boosting and different adjuvant strategies have been particularly promising but, these early clinical trial results will require confirmatory studies. Collectively, these studies suggest that clinical efficacy likely depends upon harnessing a potent vaccine combination in an appropriate clinical setting to fully realize the potential of CEA vaccination.

Indexed as

Cancer VaccinesNeoplasmsAnimalsCarcinoembryonic AntigenGenetic VectorsHumansMiceMice, Inbred C57BLVaccinationVaccines, SyntheticCancer VaccinesCarcinoembryonic AntigenVaccines, Syntheticcancer vaccinesCarcinoembryonic antigenCEAclinical trialsheterologous boostingimmunotherapyself-replicating RNA

Identifiers

PMID38087989
PMCPMC10732609
OpenAlexW4389681376

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.